Search Results - (( data classification problems algorithm ) OR ( data visualization learning algorithm ))
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Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R
Published 2020“…Besides, this paper also enlightens on one of the Machine Learning tools used which is R, with the utilization of K Nearest Neighbor (KNN) algorithm as method of classification for data. …”
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Final Year Project -
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Proceeding Paper -
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Conference or Workshop Item -
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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Article -
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Comparative analysis of danger theory variants in measuring risk level for text spam messages
Published 2024journal::journal article -
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Thesis -
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Detection of the river sediment deposition area at Kuala Perlis river mouth using Landsat 8 OLI within the years 2019, 2020 and 2021 / Nur Zakira Ain Zamrun
Published 2022“…Quantification of Landsat 8 OLI satellite images was applied using ENVI software on the study area for detecting sedimentation in the study area that used image data band correlation in deposited river sediment through unsupervised classifier algorithm and selection of spectral bands for MNDWI. …”
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Thesis -
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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Article -
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Thesis -
11
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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Thesis -
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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Article -
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A derivative-free optimization method for solving classification problem
Published 2010“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. …”
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Thesis -
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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Thesis -
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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Thesis -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…The back-propagation neural network (BPNN) algorithm performs well on many complex data types but it possess the problem of network stagnancy and local minima. …”
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